With the deepening of the development of digital technology and the innovative integration of Civic and Political Education, the traditional teaching strategy has limitations in personalized adaptation and dynamic optimization. This paper proposes an optimization algorithm for the teaching strategy of Civic and Political Education based on the hybrid intelligent optimization method. The genetic algorithm is improved by combining the dynamic generation gap optimization strategy and the phased optimization strategy, and the multi-dimensional coded fitness function model is constructed to realize the intelligent dynamic adaptation of teaching strategies. The traditional genetic algorithm reaches the optimal solution at 18 iterations, and the improved genetic algorithm is close to the optimal solution at 9 iterations. In the control test, the experimental group’s civic literacy, recognition of the teaching model, and professional literacy were higher than that of the control group, and the difference was statistically significant (P<0.05). In the experimental group, more than 85% of the students thought that the optimized teaching strategy of Civic and Political Education teaching was effective and helped to stimulate learning enthusiasm in the course of teaching. More than 95% of the students thought that the knowledge reserve, thinking ability and comprehensive quality were significantly improved by using the optimized teaching strategy of Civic and Political Education.
